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Book Ontologies for Bioinformatics

Download or read book Ontologies for Bioinformatics written by Kenneth Baclawski and published by . This book was released on 2006 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontologies as a critical framework for the vast amounts of data in the postgenomic era: an introduction to the basic concepts and applications of ontologies and ontology languages for the life sciences. Recent advances in biotechnology, spurred by the Human Genome Project, have resulted in the accumulation of vast amounts of new data. Ontologies--computer-readable, precise formulations of concepts (and the relationship among them) in a given field--are a critical framework for coping with the exponential growth of valuable biological data generated by high-output technologies. This book introduces the key concepts and applications of ontologies and ontology languages in bioinformatics and will be an essential guide for bioinformaticists, computer scientists, and life science researchers.The three parts of Ontologies for Bioinformatics ask, and answer, three pivotal questions: what ontologies are; how ontologies are used; and what ontologies could be (which focuses on how ontologies could be used for reasoning with uncertainty). The authors first introduce the notion of an ontology, from hierarchically organized ontologies to more general network organizations, and survey the best-known ontologies in biology and medicine. They show how to construct and use ontologies, classifying uses into three categories: querying, viewing, and transforming data to serve diverse purposes. Contrasting deductive, or Boolean, logic with inductive reasoning, they describe the goal of a synthesis that supports both styles of reasoning. They discuss Bayesian networks as a way of expressing uncertainty, describe data fusion, and propose that the World Wide Web can be extended to support reasoning with uncertainty. They call this inductive reasoning web the Bayesian web.

Book Introduction to Bio Ontologies

Download or read book Introduction to Bio Ontologies written by Peter N. Robinson and published by CRC Press. This book was released on 2011-06-22 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Bio-Ontologies explores the computational background of ontologies. Emphasizing computational and algorithmic issues surrounding bio-ontologies, this self-contained text helps readers understand ontological algorithms and their applications.The first part of the book defines ontology and bio-ontologies. It also explains the importan

Book Anatomy Ontologies for Bioinformatics

Download or read book Anatomy Ontologies for Bioinformatics written by Albert Burger and published by Springer Science & Business Media. This book was released on 2007-12-20 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a timely and first-of-its-kind collection of papers on anatomy ontologies. It is interdisciplinary in its approach, bringing together the relevant expertise from computing and biomedical studies. The book aims to provide readers with a comprehensive understanding of the foundations of anatomical ontologies and the-state-of-the-art in terms of existing tools and applications. It also highlights challenges that remain today.

Book Biological Ontologies and Semantic Biology

Download or read book Biological Ontologies and Semantic Biology written by John Hancock and published by Frontiers Media SA. This book was released on 2014-10-03 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the amount of biological information and its diversity accumulates massively there is a critical need to facilitate the integration of this data to allow new and unexpected conclusions to be drawn from it. The Semantic Web is a new wave of web- based technologies that allows the linking of data between diverse data sets via standardised data formats (“big data”). Semantic Biology is the application of semantic web technology in the biological domain (including medical and health informatics). The Special Topic encompasses papers in this very broad area, including not only ontologies (development and applications), but also text mining, data integration and data analysis making use of the technologies of the Semantic Web. Ontologies are a critical requirement for such integration as they allow conclusions drawn about biological experiments, or descriptions of biological entities, to be understandable and integratable despite being contained in different databases and analysed by different software systems. Ontologies are the standard structures used in biology, and more broadly in computer science, to hold standardized terminologies for particular domains of knowledge. Ontologies consist of sets of standard terms, which are defined and may have synonyms for ease of searching and to accommodate different usages by different communities. These terms are linked by standard relationships, such as “is_a” (an eye “is_a” sense organ) or “part_of” (an eye is “part_of” a head). By linking terms in this way, more detailed, or granular, terms can be linked to broader terms, allowing computation to be carried out that takes these relationships into account.

Book Information Theoretic Evaluation for Computational Biomedical Ontologies

Download or read book Information Theoretic Evaluation for Computational Biomedical Ontologies written by Wyatt Travis Clark and published by Springer Science & Business Media. This book was released on 2014-01-09 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of effective methods for the prediction of ontological annotations is an important goal in computational biology, yet evaluating their performance is difficult due to problems caused by the structure of biomedical ontologies and incomplete annotations of genes. This work proposes an information-theoretic framework to evaluate the performance of computational protein function prediction. A Bayesian network is used, structured according to the underlying ontology, to model the prior probability of a protein's function. The concepts of misinformation and remaining uncertainty are then defined, that can be seen as analogs of precision and recall. Finally, semantic distance is proposed as a single statistic for ranking classification models. The approach is evaluated by analyzing three protein function predictors of gene ontology terms. The work addresses several weaknesses of current metrics, and provides valuable insights into the performance of protein function prediction tools.

Book Bioinformatics

    Book Details:
  • Author : Kenneth Baclawski & Tianhua Niu
  • Publisher :
  • Release : 2006-01-01
  • ISBN : 9788179926420
  • Pages : 440 pages

Download or read book Bioinformatics written by Kenneth Baclawski & Tianhua Niu and published by . This book was released on 2006-01-01 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in biotechnology, spurred by the Human Genome Project, have resulted in the accumulation of vast amounts of new data. Ontologies computer-readable, precise formulations of concepts (and the relationship among them) in a given field are a critical framework for coping with the exponential growth of valuable biological data generated by high-output technologies. This book introduces the key concepts and applications of ontologies and ontology languages in bioinformatics and will be an essential guide for bioinformaticists, computer scientists, and life science researchers.The three parts of Ontologies for Bioinformatics ask, and answer, three pivotal questions: what ontologies are; how ontologies are used; and what ontologies could be (which focuses on how ontologies could be used for reasoning with uncertainty). The authors first introduce the notion of an ontology, from hierarchically organized ontologies to more general network organizations, and survey the best-known ontologies in biology and medicine. They show how to construct and use ontologies, classifying uses into three categories: querying, viewing, and transforming data to serve diverse purposes. Contrasting deductive, or Boolean, logic with inductive reasoning, they describe the goal of a synthesis that supports both styles of reasoning. They discuss Bayesian networks as a way of expressing uncertainty, describe data fusion, and propose that the World Wide Web can be extended to support reasoning with uncertainty. They call this inductive reasoning web the Bayesian web.

Book Anatomy Ontologies for Bioinformatics

Download or read book Anatomy Ontologies for Bioinformatics written by Albert Burger and published by Springer. This book was released on 2009-10-12 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a timely and first-of-its-kind collection of papers on anatomy ontologies. It is interdisciplinary in its approach, bringing together the relevant expertise from computing and biomedical studies. The book aims to provide readers with a comprehensive understanding of the foundations of anatomical ontologies and the-state-of-the-art in terms of existing tools and applications. It also highlights challenges that remain today.

Book The Gene Ontology Handbook

Download or read book The Gene Ontology Handbook written by Christophe Dessimoz and published by . This book was released on 2020-10-08 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a practical and self-contained overview of the Gene Ontology (GO), the leading project to organize biological knowledge on genes and their products across genomic resources. Written for biologists and bioinformaticians, it covers the state-of-the-art of how GO annotations are made, how they are evaluated, and what sort of analyses can and cannot be done with the GO. In the spirit of the Methods in Molecular Biology book series, there is an emphasis throughout the chapters on providing practical guidance and troubleshooting advice. Authoritative and accessible, The Gene Ontology Handbook serves non-experts as well as seasoned GO users as a thorough guide to this powerful knowledge system. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Book Semantic Web

    Book Details:
  • Author : Christopher J. O. Baker
  • Publisher : Springer Science & Business Media
  • Release : 2007-04-14
  • ISBN : 0387484388
  • Pages : 449 pages

Download or read book Semantic Web written by Christopher J. O. Baker and published by Springer Science & Business Media. This book was released on 2007-04-14 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces advanced semantic web technologies, illustrating their utility and highlighting their implementation in biological, medical, and clinical scenarios. It covers topics ranging from database, ontology, and visualization to semantic web services and workflows. The volume also details the factors impacting on the establishment of the semantic web in life science and the legal challenges that will impact on its proliferation.

Book Data Mining in Biomedicine Using Ontologies

Download or read book Data Mining in Biomedicine Using Ontologies written by Mihail Popescu and published by Artech House. This book was released on 2009 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presently, a growing number of ontologies are being built and used for annotating data in biomedical research. Thanks to the tremendous amount of data being generated, ontologies are now being used in numerous ways, including connecting different databases, refining search capabilities, interpreting experimental/clinical data, and inferring knowledge. This cutting-edge resource introduces you to latest developments in bio-ontologies. The book provides you with the theoretical foundations and examples of ontologies, as well as applications of ontologies in biomedicine, from molecular levels to clinical levels. You also find details on technological infrastructure for bio-ontologies. This comprehensive, one-stop volume presents a wide range of practical bio-ontology information, offering you detailed guidance in the clustering of biological data, protein classification, gene and pathway prediction, and text mining. More than 160 illustrations support key topics throughout the book.

Book Handbook on Ontologies

    Book Details:
  • Author : Steffen Staab
  • Publisher : Springer Science & Business Media
  • Release : 2010-03-14
  • ISBN : 3540926739
  • Pages : 809 pages

Download or read book Handbook on Ontologies written by Steffen Staab and published by Springer Science & Business Media. This book was released on 2010-03-14 with total page 809 pages. Available in PDF, EPUB and Kindle. Book excerpt: An ontology is a formal description of concepts and relationships that can exist for a community of human and/or machine agents. The notion of ontologies is crucial for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies considering ontology languages, ontology engineering methods, example ontologies, infrastructures and technologies for ontologies, and how to bring this all into ontology-based infrastructures and applications that are among the best of their kind. The field of ontologies has tremendously developed and grown in the five years since the first edition of the "Handbook on Ontologies". Therefore, its revision includes 21 completely new chapters as well as a major re-working of 15 chapters transferred to this second edition.

Book Knowledge Based Bioinformatics

Download or read book Knowledge Based Bioinformatics written by Gil Alterovitz and published by John Wiley & Sons. This book was released on 2011-04-20 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an increasing need throughout the biomedical sciences for a greater understanding of knowledge-based systems and their application to genomic and proteomic research. This book discusses knowledge-based and statistical approaches, along with applications in bioinformatics and systems biology. The text emphasizes the integration of different methods for analysing and interpreting biomedical data. This, in turn, can lead to breakthrough biomolecular discoveries, with applications in personalized medicine. Key Features: Explores the fundamentals and applications of knowledge-based and statistical approaches in bioinformatics and systems biology. Helps readers to interpret genomic, proteomic, and metabolomic data in understanding complex biological molecules and their interactions. Provides useful guidance on dealing with large datasets in knowledge bases, a common issue in bioinformatics. Written by leading international experts in this field. Students, researchers, and industry professionals with a background in biomedical sciences, mathematics, statistics, or computer science will benefit from this book. It will also be useful for readers worldwide who want to master the application of bioinformatics to real-world situations and understand biological problems that motivate algorithms.

Book Applied Ontology

    Book Details:
  • Author : Katherine Munn
  • Publisher : Walter de Gruyter
  • Release : 2013-05-02
  • ISBN : 3110324865
  • Pages : 342 pages

Download or read book Applied Ontology written by Katherine Munn and published by Walter de Gruyter. This book was released on 2013-05-02 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontology is the philosophical discipline which aims to understand how things in the world are divided into categories and how these categories are related together. This is exactly what information scientists aim for in creating structured, automated representations, called ‘ontologies,’ for managing information in fields such as science, government, industry, and healthcare. Currently, these systems are designed in a variety of different ways, so they cannot share data with one another. They are often idiosyncratically structured, accessible only to those who created them, and unable to serve as inputs for automated reasoning. This volume shows, in a non-technical way and using examples from medicine and biology, how the rigorous application of theories and insights from philosophical ontology can improve the ontologies upon which information management depends.

Book Introduction to Bioinformatics

Download or read book Introduction to Bioinformatics written by Attwood and published by Pearson Education India. This book was released on 1999 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Anatomy Ontologies for Bioinformatics

Download or read book Anatomy Ontologies for Bioinformatics written by Albert G. Burger and published by . This book was released on 2008 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a collection of papers on anatomy ontologies. This book aims to provide readers with a comprehensive understanding of the foundations of anatomical ontologies and the-state-of-the-art in terms of tools and applications.

Book Semantic Similarity from Natural Language and Ontology Analysis

Download or read book Semantic Similarity from Natural Language and Ontology Analysis written by Sébastien Harispe and published by Morgan & Claypool Publishers. This book was released on 2015-05-01 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better understanding of semantic similarity estimation and more generally semantic measures. To this end, we propose an in-depth characterization of existing proposals by discussing their features, the assumptions on which they are based and empirical results regarding their performance in particular applications. By answering these questions and by providing a detailed discussion on the foundations of semantic measures, our aim is to give the reader key knowledge required to: (i) select the more relevant methods according to a particular usage context, (ii) understand the challenges offered to this field of study, (iii) distinguish room of improvements for state-of-the-art approaches and (iv) stimulate creativity toward the development of new approaches. In this aim, several definitions, theoretical and practical details, as well as concrete applications are presented

Book Algorithms in Structural Molecular Biology

Download or read book Algorithms in Structural Molecular Biology written by Bruce R. Donald and published by MIT Press. This book was released on 2023-08-15 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field.